test
RAD
| test | RAD | |
|---|---|---|
| 9 | 3 | |
| 933 | 180 | |
| - | - | |
| 2.5 | 4.5 | |
| 11 months ago | 5 months ago | |
| Python | HTML | |
| MIT License | GNU General Public License v3.0 or later |
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test
- Measuring Multitask Language Understanding
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Mixtral 7B MoE beats LLaMA2 70B in MMLU
Sources [1] MMLU Benchmark (Multi-task Language Understanding) | Papers With Code https://paperswithcode.com/sota/multi-task-language-understanding-on-mmlu [2] MMLU Dataset | Papers With Code https://paperswithcode.com/dataset/mmlu [3] hendrycks/test: Measuring Massive Multitask Language Understanding | ICLR 2021 - GitHub https://github.com/hendrycks/test [4] lukaemon/mmlu · Datasets at Hugging Face https://huggingface.co/datasets/lukaemon/mmlu [5] [2009.03300] Measuring Massive Multitask Language Understanding - arXiv https://arxiv.org/abs/2009.03300
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BREAKING: Google just released its ChatGPT Killer
With a score of 90.0%, Gemini Ultra is the first model to outperform human experts on MMLU (massive multitask language understanding), which uses a combination of 57 subjects such as math, physics, history, law, medicine and ethics for testing both world knowledge and problem-solving abilities.
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[Colab Notebook] Launch quantized MPT-30B-Chat on Vast.ai using text-generation-inference, integrated with ConversationChain
One method for comparison is the MMLU https://arxiv.org/abs/2009.03300.
- Partial Solution To AI Hallucinations
- Announcing GPT-4.
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Show HN: Llama-dl – high-speed download of LLaMA, Facebook's 65B GPT model
Because there are many benchmarks that measure different things.
You need to look at the benchmark that reflects your specific interest.
So in this case ("I wasn't impressed that 30B didn't seem to know who Captain Picard was") the closest relevant benchmark they performed is MMLU (Massive Multitask Language Understanding"[1].
In the LLAMA paper they publish a figure of 63.4% for the 5-shot average setting without fine tuning on the 65B model, and 68.9% after fine tuning. This is significantly better that the original GPT-3 (43.9% under the same conditions) but as they note:
> "[it is] still far from the state-of-the-art, that is 77.4 for GPT code-davinci-002 on MMLU (numbers taken from Iyer et al. (2022))"
InstructGPT[2] (which OpenAI points at as most relevant ChatGPT publication) doesn't report MMLU performance.
[1] https://github.com/hendrycks/test
[2] https://arxiv.org/abs/2203.02155
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DeepMind's newest language model, Chinchilla (70B parameters), significantly outperforms Gopher (280B) and GPT-3 (175B) on a large range of downstream evaluation tasks
Benchmark result is 67.6% which is 7.6% improvement from Gopher. MMLU is multiple choice Q&A over various subjects. Questions can be found linked in this github repo (see data).
RAD
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Im going to get a Commodore 64
Can you tell me if this expansion card is worth it? https://github.com/frntc/RAD I have an original c64 and just need a drive to load and save software. I saw the ultimate, but I'm not sure if I should shell out that many cash. The rad would cost me 60€ the ultimate about 170€.
- C64 reu for €20?
- Just finished my latest build, a RAD Expansion Unit... and yes it does work with Sonic!
What are some alternatives?
mmfewshot - OpenMMLab FewShot Learning Toolbox and Benchmark
Sidekick64 - Sidekick64: A Versatile Software-Defined Cartridge for the C64, C128, C16, plus/4, and VIC20
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
Flutter - Flutter makes it easy and fast to build beautiful apps for mobile and beyond
ut - C++20 μ(micro)/Unit Testing Framework
PiInk - An E-Ink digital picture frame that gives images a natural aesthetic.
elm-test-rs - Fast and portable executable to run your Elm tests
test - A library for writing unit tests in Dart.
egghead - discord bot for ai stuff
jaspr - Modern web framework for building websites in Dart. Supports SPAs and SSR.
llama-int8 - Quantized inference code for LLaMA models
chilipie-kiosk - Easy-to-use Raspberry Pi image for booting directly into full-screen Chrome, with built-in convenience features for unattended operation. Perfect for dashboards and build monitors.